Modeling and predicting application performance on parallel computers using HPC challenge benchmarks

A method is presented for modeling application performance on parallel computers in terms of the performance of microkernels from the HPC Challenge benchmarks. Specifically, the application run time is expressed as a linear combination of inverse speeds and latencies from microkernels or system characteristics. The model parameters are obtained by an automated series of least squares fits using backward elimination to ensure statistical significance. If necessary, outliers are deleted to ensure that the final fit is robust. Typically three or four terms appear in each model: at most one each for floating-point speed, memory bandwidth, interconnect bandwidth, and interconnect latency. Such models allow prediction of application performance on future computers from easier-to-make predictions of microkernel performance. The method was used to build models for four benchmark problems involving the PARATEC and MILC scientific applications. These models not only describe performance well on...

• Type: Conference
• Year: 2008
• Where: IPPS
• Authors: Wayne Pfeiffer, Nicholas J. Wright
• Keywords: Application Performance, Benchmark Problems, Distributed And Parallel Computing, IPPS 2008, Run Times